Optimal medical decision making requires consideration of efficacy and toxicity data, patient preferences and cost-effectiveness information. Working examining the synthesis of these considerations into actual choices made by patients and clinicians is limited. The candidate will focus her research on this interface of outcomes data and clinical decision making using bone marrow transplantation as a model. The specific research aims of this proposal are to: 1. Examine the knowledge, values, expectations and decision making processes of patients undergoing bone marrow transplantation using a prospective, longitudinal, questionnaire-based design. Results will allow her to analyze the influence of these considerations on decision making. 2. Use decision analytic techniques to synthesize the complex trade-offs inherent in the use of unrelated donor bone marrow transplantation for the treatment of chronic myelogenous leukemia. Results will be used to determine the best method of communicating complex outcome information to assist patient and clinician decision making. Completion of these projects will improve our understanding of how and why patients make health care decisions that what can be done to assist them in making difficult choices. In addition, this proposal will give the candidate experience in study design and implementation, decision analysis, instrument development, and measurement of pateint preferences. This research will be conducted in the Center for Outcomes and Policy Research, an environment supported by faculty from the Harvard School of Public Health, the Dana-Farber Cancer Institute, the Harvard Center for Risk Analysis, and the Brigham and Women's Hospital. These collaborations will assure interactions vital to the success of these projects and to the candidate's career. Since medical decision making also requires an understanding of efficacy data and the psychology of decision making, classwork at the Harvard School of Public Health will provide exposure to case-control and cohort studies, meta-analysis, biostatistics, decision theory and risk analysis.